A gene controlling sex in grapevines placed on a molecular marker-based genetic map
Bibliographic record
Abstract
Genetic maps of Vitis (2n = 38) have been constructed from an interspecific hybrid population of 58 seedlings of the cross 'Horizon' ('Seyval' x 'Schuyler') x Illinois 547-1 (V. cinerea B9 x V. rupestris B38). The maps were initially constructed based on 277 RAPD (random amplified polymorphic DNA) markers using a double-pseudotestcross strategy. Subsequently, 25 microsatellites, 4 CAPS (cleaved amplified polymorphic sequence), and 12 AFLP (amplified fragment length polymorphism) markers were added to the maps. Another 120 markers, mostly those segregating 3:1, were also assigned but not positioned on the linkage groups in the two maps. The 'Horizon' map consisted of 153 markers covering 1199 cM, with an average map distance of 7.6 cM between markers. The Illinois 547-1 map had 179 markers covering 1470 cM, with an average map distance of 8.1 cM. There were 20 linkage groups in each map, one more than the basic number of chromosomes in grapes. Ten linkage groups in each map were identified as homologous using 16 microsatellite and 2 CAPS markers polymorphic in both parents. A single locus controlling sex in grapes mapped close to a microsatellite marker. These maps provide enough coverage of the genome for QTL (quantitative trait loci) analysis and as a starting point for positional gene cloning in grapes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".